Online Detection of Golden Circuit Cutting Points

TL;DR

This paper introduces the concept of golden cutting points in quantum circuit cutting, which optimizes the reconstruction process by identifying unnecessary basis components, thereby reducing computational resources and improving simulation efficiency.

Contribution

It proposes a hypothesis-testing scheme to identify golden cutting points and demonstrates its effectiveness on Qiskit's Aer simulator, reducing wall time and computational overhead.

Findings

Reduced wall time in quantum circuit simulation

Effective identification of unnecessary basis components

Improved efficiency in quantum circuit reconstruction

Abstract

Quantum circuit cutting has emerged as a promising method for simulating large quantum circuits using a collection of small quantum machines. Running low-qubit "circuit fragments" not only overcomes the size limitation of near-term hardware, but it also increases the fidelity of the simulation. However, reconstructing measurement statistics requires computational resources - both classical and quantum - that grow exponentially with the number of cuts. In this manuscript, we introduce the concept of a golden cutting point, which identifies unnecessary basis components during reconstruction and avoids related down-stream computation. We propose a hypothesis-testing scheme for identifying golden cutting points, and provide robustness results in the case of the test failing with low probability. Lastly, we demonstrate the applicability of our method on Qiskit's Aer simulator and observe a reduced wall time from identifying and avoiding obsolete measurements.